✦ LIBER ✦

Multivariate Prediction with Nonlinear Principal Components Analysis: Application

✍ Scribed by JÖRG BLASIUS; JOHN C. GOWER

Publisher: Springer Netherlands
Year: 2005
Tongue: English
Weight: 346 KB
Volume: 39
Category: Article
ISSN: 0033-5177
DOI: 10.1007/s11135-005-3006-0

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Multivariate Prediction with Nonlinear P

Multivariate Prediction with Nonlinear Principal Components Analysis: Theory

✍ JOHN C. GOWER; JÖRG BLASIUS 📂 Article 📅 2005 🏛 Springer Netherlands 🌐 English ⚖ 216 KB

Multivariate response surface modelling

Multivariate response surface modelling by principal components analysis

✍ N. Bratchell 📂 Article 📅 1989 🏛 John Wiley and Sons 🌐 English ⚖ 580 KB

Multivariate data reduction by principal

Multivariate data reduction by principal components, with application to neurological scoring instruments

✍ J. A. Koziol; W. Hacke 📂 Article 📅 1990 🏛 Springer 🌐 English ⚖ 454 KB

Principal components analysis is widely used as a practical tool for the analysis of multivariate data. The aim of this analysis is to reduce the dimensionality of a multivariate data set to the smallest number of meaningful and independent dimensions. The analysis can also provide interpretable lin

Batch tracking via nonlinear principal c

Batch tracking via nonlinear principal component analysis

✍ Dong Dong; Thomas J. McAvoy 📂 Article 📅 1996 🏛 American Institute of Chemical Engineers 🌐 English ⚖ 842 KB

Principal Component Analysis from the Mu

Principal Component Analysis from the Multivariate Familial Correlation Matrix

✍ Martin Bilodeau; Pierre Duchesne 📂 Article 📅 2002 🏛 Elsevier Science 🌐 English ⚖ 123 KB

This paper considers principal component analysis (PCA) in familial models, where the number of siblings can differ among families.

A multivariate principal component regre

A multivariate principal component regression analysis of NIR data

✍ Jianguo Sun 📂 Article 📅 1996 🏛 John Wiley and Sons 🌐 English ⚖ 564 KB

The analysis of near-infrared (NIR) data arising from NIR experiments in which there exists more than one response variable of interest is discussed,with focus on the investigation of the relationship of response variables. A multivariate regression procedure based on principal component regression